Triple

T1226513
Position Surface form Disambiguated ID Type / Status
Subject Madrid Metro E26338 entity
Predicate connectsWith P37 FINISHED
Object Cercanías Madrid E26548 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Cercanías Madrid | Statement: [Madrid Metro, connectsWith, Cercanías Madrid]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cercanías Madrid
Context triple: [Madrid Metro, connectsWith, Cercanías Madrid]
  • A. Cercanías Madrid commuter rail chosen
    Cercanías Madrid commuter rail is a regional train network that connects Madrid with its surrounding metropolitan and suburban areas, providing frequent and rapid transit for daily commuters.
  • B. Metro Ligero de Madrid
    Metro Ligero de Madrid is a light rail system serving several suburban and peripheral areas of Madrid, complementing the city's main metro network.
  • C. Madrid Metro
    Madrid Metro is the extensive rapid transit system serving Spain’s capital, known for its large network, frequent service, and role as a primary mode of urban transportation.
  • D. Seville Metro
    Seville Metro is a rapid transit system serving the city of Seville and its metropolitan area in southern Spain.
  • E. Barcelona Metro
    Barcelona Metro is the rapid transit rail network serving the city of Barcelona and its metropolitan area, known for its extensive coverage and integration with other public transport modes.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a49484688c8190a1bf285eb396a8b6 completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be39908481908cca21aaf0828415 completed March 1, 2026, 10:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac8f7391408190928cab62e34aa361 completed March 7, 2026, 8:49 p.m.
Created at: March 1, 2026, 7:47 p.m.